activity
20162019
most citedSelective Sensor Fusion for Neural Visual-Inertial Odometry

6 citations · 6 across the 2 of their papers we have counts for

collaborators

6 papers

cs.CV2019

RandLA-Net: Efficient Semantic Segmentation of Large-Scale Point Clouds

Qingyong Hu, Bo Yang, Linhai Xie +5

We study the problem of efficient semantic segmentation for large-scale 3D point clouds. By relying on expensive sampling techniques or computationally heavy pre/post-processing st…

eess.SP2019

See Through Smoke: Robust Indoor Mapping with Low-cost mmWave Radar

Chris Xiaoxuan Lu, Stefano Rosa, Peijun Zhao +5

This paper presents the design, implementation and evaluation of milliMap, a single-chip millimetre wave (mmWave) radar based indoor mapping system targetted towards low-visibility…

cs.CV2019

DeepTIO: A Deep Thermal-Inertial Odometry with Visual Hallucination

Muhamad Risqi U. Saputra, Pedro P. B. de Gusmao, Chris Xiaoxuan Lu +7

Visual odometry shows excellent performance in a wide range of environments. However, in visually-denied scenarios (e.g. heavy smoke or darkness), pose estimates degrade or even fa…

cs.CV20196 cited

Selective Sensor Fusion for Neural Visual-Inertial Odometry

Changhao Chen, Stefano Rosa, Yishu Miao +4

Deep learning approaches for Visual-Inertial Odometry (VIO) have proven successful, but they rarely focus on incorporating robust fusion strategies for dealing with imperfect input…

cs.RO2018

Learning with Training Wheels: Speeding up Training with a Simple Controller for Deep Reinforcement Learning

Linhai Xie, Sen Wang, Stefano Rosa +2

Deep Reinforcement Learning (DRL) has been applied successfully to many robotic applications. However, the large number of trials needed for training is a key issue. Most of existi…

cs.CV2016

Fast Graph-Based Object Segmentation for RGB-D Images

Giorgio Toscana, Stefano Rosa

Object segmentation is an important capability for robotic systems, in particular for grasping. We present a graph- based approach for the segmentation of simple objects from RGB-D…